aeolus_amv.py 11.60 KiB
import datetime, os
from datetime import timezone
import glob
import numpy as np
from netCDF4 import Dataset, Dimension, Variable
from aeolus.geos_nav import GEOSNavigation
from util.util import haversine_np
amv_file_duration = 60 # minutes
half_width = 20 # search box centered on AEOLUS profile (FGF coordinates)
num_elems = 5424
num_lines = 5424
first_time = True
ftimes = []
flist = None
class MyGenericException(Exception):
def __init__(self, message):
self.message = message
def get_datetime(pathname):
fname = os.path.split(pathname)[1]
toks = fname.split('_')
dstr = toks[4]
tstr = toks[5]
dtstr = dstr+tstr
dto = datetime.datetime.strptime(dtstr, '%Y%j%H%M').replace(tzinfo=timezone.utc)
return dto
def get_datetime_ops(pathname):
fname = os.path.split(pathname)[1]
toks = fname.split('_')
dtstr = toks[3]
dtstr = dtstr[:-3]
dto = datetime.datetime.strptime(dtstr, 's%Y%j%H%M').replace(tzinfo=timezone.utc)
return dto
def get_datetime_carr(pathname):
fname = os.path.split(pathname)[1]
toks = fname.split('_')
dtstr = toks[3]
dto = datetime.datetime.strptime(dtstr, '%Y%j.%H%M.ch').replace(tzinfo=timezone.utc)
return dto
def get_file_containing_time(timestamp, files_path, file_time_span, amv_source='OPS', band='14'):
global first_time, ftimes, flist
if first_time is True:
if amv_source == 'OPS':
flist = glob.glob(files_path + 'OR_ABI-L2-DMWF*'+'C'+band+'*.nc')
dto_func = get_datetime_ops
elif amv_source == 'SSEC':
flist = glob.glob(files_path + '*WINDS_AMV_EN-'+band+'*.nc')
dto_func = get_datetime
elif amv_source == 'CARR':
flist = glob.glob(files_path + 'tdw_qc_GOES*'+'ch_'+band+'.nc')
dto_func = get_datetime_carr
for pname in flist: # TODO: make better with regular expressions (someday)
dto = dto_func(pname)
dto_start = dto
dto_end = dto + datetime.timedelta(minutes=file_time_span)
ftimes.append((dto_start.timestamp(), dto_end.timestamp()))
first_time = False
k = -1
for i in range(len(ftimes)):
if (timestamp >= ftimes[i][0]) and (timestamp < ftimes[i][1]):
k = i
break
if k < 0:
return None, None, None
return flist[k], ftimes[k], k
# imports the S4 NOAA output
# filename: full path as a string, '/home/user/filename'
# returns a dict: time -> list of profiles (a profile is a list of levels)
def get_aeolus_time_dict(filename, lon360=False, do_sort=True):
time_dict = {}
with open(filename) as file:
while True:
prof_hdr = file.readline()
if not prof_hdr:
break
toks = prof_hdr.split()
yr = int(float(toks[0]))
mon = int(float(toks[1]))
dy = int(float(toks[2]))
hr = int(float(toks[3]))
mn = int(float(toks[4]))
ss = int(float(toks[5]))
lon = float(toks[6])
lat = float(toks[7])
nlevs = int(toks[8])
if lon360:
if lon < 0:
lon += 360.0
else:
if lon > 180.0:
lon -= 360.0
dto = datetime.datetime(year=yr, month=mon, day=dy, hour=hr, minute=mn, second=ss)
dto = dto.replace(tzinfo=timezone.utc)
timestamp = dto.timestamp()
prof = []
if time_dict.get(timestamp, -1) == -1:
prof_s = []
prof_s.append(prof)
time_dict[timestamp] = prof_s
else:
prof_s = time_dict.get(timestamp)
prof_s.append(prof)
for k in range(nlevs):
line = file.readline()
toks = line.split()
lvlidx = int(toks[0])
hhh = float(toks[1]) * 1000.0
hht = float(toks[2]) * 1000.0
hhb = float(toks[3]) * 1000.0
err = float(toks[4])
azm = float(toks[5])
ws = float(toks[6])
len = float(toks[7])
tup = (lat, lon, hhh, hht, hhb, azm, ws)
prof.append(tup)
file.close()
if do_sort:
keys = np.array(list(time_dict.keys()))
keys.sort()
keys = keys.tolist()
sorted_time_dict = {}
for key in keys:
sorted_time_dict[key] = time_dict.get(key)
time_dict = sorted_time_dict
return time_dict
# make each profile at a timestamp a numpy array
def time_dict_to_nd(time_dict):
keys = list(time_dict.keys())
for key in keys:
vals = time_dict[key]
if vals is not None:
for i in range(len(vals)):
nda = np.array(vals[i])
vals[i] = nda
return time_dict
def concat(t_dct_0, t_dct_1):
keys_0 = list(t_dct_0.keys())
nda_0 = np.array(keys_0)
keys_1 = list(t_dct_1.keys())
nda_1 = np.array(keys_1)
comm_keys, comm0, comm1 = np.intersect1d(nda_0, nda_1, return_indices=True)
comm_keys = comm_keys.tolist()
for key in comm_keys:
t_dct_1.pop(key)
t_dct_0.update(t_dct_1)
return t_dct_0
def get_aeolus_time_dict_s(filenames, lon360=False, do_sort=True):
dct_s = []
for fname in filenames:
a_dct = get_aeolus_time_dict(fname, lon360=lon360, do_sort=do_sort)
t_dct = time_dict_to_nd(a_dct)
dct_s.append(t_dct)
t_dct = dct_s[0]
for dct in dct_s[1:]:
concat(t_dct, dct)
return t_dct
def run_amv_aeolus_best_fit(match_dict):
return None
def get_search_box(nav, lon, lat):
cc, ll = nav.earth_to_lc(lon, lat)
if cc is None:
return None, None
c_rng = [cc - half_width, cc + half_width]
l_rng = [ll - half_width, ll + half_width]
if c_rng[0] < 0:
c_rng[0] = 0
if l_rng[0] < 0:
l_rng[0] = 0
if c_rng[1] >= num_elems:
c_rng[1] = num_elems - 1
if l_rng[1] >= num_lines:
l_rng[1] = num_lines - 1
return c_rng, l_rng
# Framework
amv_dir_name = 'Wind_Dir'
amv_spd_name = 'Wind_Speed'
amv_lon_name = 'Longitude'
amv_lat_name = 'Latitude'
amv_elem_name = 'Element'
amv_line_name = 'Line'
amv_press_name = 'MedianPress'
# -------------------------------
# Carr stereo
amv_lon_name = 'Lon'
amv_lat_name = 'Lat'
amv_press_name = 'pres'
# -------------------------------
sub_lon = -137.0 # GOES-17
#sub_lon = -75.0 # GOES-16
# aeolus_dict: time -> profiles
# amv_files_path: directory containing AMVs, '/home/user/amvdir/'
# return dict: aeolus time -> tuple (amv_lon, amv_lat, amv_pres, amv_spd, amv_dir)
def match_amvs_to_aeolus(aeolus_dict, amv_files_path, amv_source='OPS', band='14'):
nav = GEOSNavigation(sub_lon=sub_lon)
match_dict = {}
keys = list(aeolus_dict.keys())
last_f_idx = -1
for key in keys:
fname, ftime, f_idx = get_file_containing_time(key, amv_files_path, amv_file_duration, amv_source, band)
if f_idx is None:
continue
profs = aeolus_dict.get(key)
layers = profs[0]
if layers is None:
continue
lat = layers[0, 0]
lon = layers[0, 1]
c_rng, l_rng = get_search_box(nav, lon, lat)
if c_rng is None:
continue
if f_idx != last_f_idx:
last_f_idx = f_idx
ds = Dataset(fname)
amv_lons = ds[amv_lon_name][:]
amv_lats = ds[amv_lat_name][:]
amv_spd = ds[amv_spd_name][:]
amv_dir = ds[amv_dir_name][:]
amv_pres = ds[amv_press_name][:]
cc = ds[amv_elem_name][:]
ll = ds[amv_line_name][:]
# cc, ll = nav.earth_to_lc_s(amv_lons, amv_lats)
ds.close()
in_cc = np.logical_and(cc > c_rng[0], cc < c_rng[1])
in_ll = np.logical_and(ll > l_rng[0], ll < l_rng[1])
in_box = np.logical_and(in_cc, in_ll)
num_amvs = np.sum(in_box)
if num_amvs == 0:
continue
dist = haversine_np(lon, lat, amv_lons[in_box], amv_lats[in_box])
match_dict[key] = (amv_lons[in_box], amv_lats[in_box], amv_pres[in_box], amv_spd[in_box], amv_dir[in_box], dist)
return match_dict
# full path as string filename to create, '/home/user/newfilename'
# aeolus_to_amv_dct: output from match_amvs_to_aeolus
# aeolus_dct: output from get_aeolus_time_dict
def create_file(filename, aeolus_to_amv_dct, aeolus_dct):
keys = list(aeolus_to_amv_dct.keys())
num_amvs = []
num_levs = []
times = []
namvs = 0
nlevs = 0
for key in keys:
lons, lats, pres, spd, dir, dist = aeolus_to_amv_dct.get(key)
num_amvs.append(len(lons))
namvs += len(lons)
prof_s = aeolus_dct.get(key)
prof = prof_s[0]
num_levs.append(prof.shape[0])
nlevs += prof.shape[0]
times.append(key)
amv_per_alus = len(aeolus_to_amv_dct)
rootgrp = Dataset(filename, 'w', format='NETCDF4')
dim_amvs = rootgrp.createDimension('amvs', size=namvs)
dim_alus = rootgrp.createDimension('profs', size=nlevs)
dim_num_aeolus_prof = rootgrp.createDimension('num_aeolus_profs', size=len(aeolus_to_amv_dct))
amv_lon = rootgrp.createVariable('amv_longitude', 'f4', ['amvs'])
amv_lon.units = 'degrees east'
amv_lat = rootgrp.createVariable('amv_latitude', 'f4', ['amvs'])
amv_lat.units = 'degrees north'
amv_spd = rootgrp.createVariable('amv_spd', 'f4', ['amvs'])
amv_spd.units = 'm s-1'
amv_dir = rootgrp.createVariable('amv_dir', 'f4', ['amvs'])
amv_dir.units = 'degree'
amv_pres = rootgrp.createVariable('amv_pres', 'f4', ['amvs'])
amv_pres.units = 'hPa'
amv_dist = rootgrp.createVariable('amv_dist', 'f4', ['amvs'])
amv_dist.units = 'km'
num_amvs_per_prof = rootgrp.createVariable('num_amvs_per_prof', 'i4', ['num_aeolus_profs'])
num_levs_per_prof = rootgrp.createVariable('num_levs_per_prof', 'i4', ['num_aeolus_profs'])
prof_time = rootgrp.createVariable('time', 'f4', ['num_aeolus_profs'])
prof_time.units = 'seconds since 1970-01-1 00:00:00'
prf_azm = rootgrp.createVariable('prof_azm', 'f4', ['profs'])
prf_azm.units = 'degree'
prf_spd = rootgrp.createVariable('prof_spd', 'f4', ['profs'])
prf_spd.units = 'm s-1'
prf_hht = rootgrp.createVariable('prof_hht', 'f4', ['profs'])
prf_hht.units = 'meter'
prf_hhb = rootgrp.createVariable('prof_hhb', 'f4', ['profs'])
prf_hhb.units = 'meter'
i_a = 0
i_c = 0
for idx, key in enumerate(keys):
namvs = num_amvs[idx]
nlevs = num_levs[idx]
i_b = i_a + namvs
i_d = i_c + nlevs
lons, lats, pres, spd, dir, _ = aeolus_to_amv_dct.get(key)
amv_lon[i_a:i_b] = lons[:]
amv_lat[i_a:i_b] = lats[:]
amv_spd[i_a:i_b] = spd[:]
amv_dir[i_a:i_b] = dir[:]
amv_pres[i_a:i_b] = pres[:]
amv_dist[i_a:i_b] = dist[:]
i_a += namvs
prof_s = aeolus_dct.get(key)
prof = prof_s[0]
prf_hht[i_c:i_d] = prof[:, 2]
prf_hhb[i_c:i_d] = prof[:, 3]
prf_azm[i_c:i_d] = prof[:, 5]
prf_spd[i_c:i_d] = prof[:, 6]
i_c += nlevs
num_amvs_per_prof[:] = num_amvs
num_levs_per_prof[:] = num_levs
prof_time[:] = times
rootgrp.close()
# aeolus_file: S4 NOAA txt output
# amv_files_dir: G16/17 AMV product file
# outfile: pathname for the Netcdf match file
def run(aeolus_file, amv_files_dir, outfile=None, amv_source='OPS', band='14'):
a_d = get_aeolus_time_dict(aeolus_file)
a_d = time_dict_to_nd(a_d)
m_d = match_amvs_to_aeolus(a_d, amv_files_dir, amv_source, band)
if outfile is not None:
create_file(outfile, m_d, a_d)